Triple
T28023977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Master Boot Record |
E707759
|
entity |
| Predicate | partitionTableEntryCount |
P171779
|
FINISHED |
| Object | 4 |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 4 | Statement: [Master Boot Record, partitionTableEntryCount, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partitionTableEntryCount Context triple: [Master Boot Record, partitionTableEntryCount, 4]
-
A.
partitionTableOffset
Indicates the position or displacement of a partition within a table relative to a defined starting point or reference.
-
B.
supportsPartitionTable
Indicates that one entity provides the capability to create, manage, or operate on partitioned tables for another entity.
-
C.
partitionTableLocation
Indicates the storage location or path where a specific table partition is physically stored or managed.
-
D.
sectorCountPerTrack
Indicates the number of data sectors that are contained on each individual track of a storage medium.
-
E.
nameTableCount
Indicates the number of tables associated with or identified by a given name.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ef96baf3a881909a2b63844185dddd |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f6a28c7c148190bfc980aad9f678ca |
completed | May 3, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69f69fe1e3c88190830bb2e9f407357e |
completed | May 3, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69f6a28b8ea881908733485374771c51 |
completed | May 3, 2026, 1:19 a.m. |
Created at: April 27, 2026, 8:11 p.m.